Imperial College London
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ProfessorDaniloMandic

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Machine Intelligence
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Nakamura:2017:10.1109/TIFS.2017.2763124,
author = {Nakamura, T and Goverdovsky, V and mandic, D},
doi = {10.1109/TIFS.2017.2763124},
journal = {IEEE Transactions on Information Forensics and Security},
pages = {648--661},
title = {In-ear EEG biometrics for feasible and readily collectable real-world person authentication},
url = {http://dx.doi.org/10.1109/TIFS.2017.2763124},
volume = {13},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The use of EEG as a biometrics modality has been investigated for about a decade, however its feasibility in real-world applications is not yet conclusively established, mainly due to the issues with collectability and reproducibility. To this end, we propose a readily deployable EEG biometrics system based on a ‘one-fits-all’ viscoelastic generic in-ear EEG sensor (collectability), which does not require skilled assistance or cumbersome preparation. Unlike most existing studies, we consider data recorded over multiple recording days and for multiple subjects (reproducibility) while, for rigour, the training and test segments are not taken from the same recording days. A robust approach is considered based on the resting state with eyes closed paradigm, the use of both parametric (autoregressive model) and non-parametric (spectral) features, and supported by simple and fast cosine distance, linear discriminant analysis and support vector machine classifiers. Both the verification and identification forensics scenarios are considered and the achieved results are on par with the studies based on impractical on-scalp recordings. Comprehensive analysis over a number of subjects, setups, and analysis features demonstrates the feasibility of the proposed ear-EEG biometrics, and its potential in resolving the critical collectability, robustness, and reproducibility issues associated with current EEG biometrics.
AU  - Nakamura,T
AU  - Goverdovsky,V
AU  - mandic,D
DO  - 10.1109/TIFS.2017.2763124
EP  - 661
PY  - 2017///
SN  - 1556-6013
SP  - 648
TI  - In-ear EEG biometrics for feasible and readily collectable real-world person authentication
T2  - IEEE Transactions on Information Forensics and Security
UR  - http://dx.doi.org/10.1109/TIFS.2017.2763124
UR  - http://hdl.handle.net/10044/1/51650
VL  - 13
ER  -
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